Airbnb Data Visualization

This is my application to the Capital One Software Engineering Summit.

It contains several charts with different statistics about Airbnb listings in San Francisco. It also has a heatmap that can be used to estimate a price for a new listing in the area. I also included some thoughts about the data and in some cases, further analysis that could be done.

Setup

First, clone from https://github.com/McIntireEvan/capital-one-summit.

Next, grab the data from here

Extract all the data, and put listings.csv in /server/data

Then, from the root directory of the project, run

cd server
npm install
node server.js

to get all the dependencies installed and the server running.

The server does not serve any static files; it just parses and returns data. To get everything properly set up with nginx, add the following to your config

upstream express-data {
    server localhost:5052;
}

server {
    listen 80; # Or whatever port you want
    server_name localhost;
    root /var/www/data-vis/static; # Or wherever you install to

    index index.html;
    location / {
        try_files $uri $uri/ @express-data;
    }

    location @express-data {
        proxy_redirect off;
        proxy_http_version 1.1;
        proxy_pass http://express-data;
        proxy_set_header Host $host ;
        proxy_set_header X-Real-IP $remote_addr;
        proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
    }
}

This tells nginx to first try to find the files, and to fall back on our express server if it can't locate it.

You'll also have to grab a Google Maps API key from here.

Once you have it, just go to the <script> tag near the bottom of index.html, find the ?key= parameter in the URL, and replace mine with yours

After this, you're done! Go to your webpage, and enjoy!

Project Structure

All the static files to be served by the webserver are in static/

The server and npm package info are in server/

Libraries Used

• Express
• csv-parse
• chart.js
• Google Maps
• haversine

Other considerations; Possible improvements

• On the server, caching the data instead of directly storing it would improve memory usage, but with the scope of the project right now is not worth it.

• When getting data to suggest a price, if there fewer data points than some threshold, it should expand the search radius until we have enough

• The CSS is a mess and could be cleaned up a lot.

• The chart options and related code could be abstracted to follow DRY